Antenna Season Report Notebook¶

Josh Dillon, Last Revised January 2022

This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.

In [1]:
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
In [2]:
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
In [3]:
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "83"
csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
In [4]:
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))

Antenna 83 Report

In [5]:
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
In [6]:
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 40 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_
Found 38 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
In [7]:
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'

Load relevant info from summary CSVs¶

In [8]:
this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
            antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
        else:
            antnum = int(row['Ant'])
        if antnum != int(antenna):
            continue
        
        if np.issubdtype(type(row['Node']), np.integer):
            row['Node'] = str(row['Node'])
        if type(row['Node']) == str and row['Node'].isnumeric():
            row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break
In [9]:
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])

Table 1: Per-Night RTP Summary Info For This Atenna¶

This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.

In [10]:
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))

Antenna 83, Node N07:

Out[10]:
JDs A Priori Status Auto Metrics Flags Dead Fraction in Ant Metrics (Jee) Dead Fraction in Ant Metrics (Jnn) Crossed Fraction in Ant Metrics Flag Fraction Before Redcal Flagged By Redcal chi^2 Fraction ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score Average Dead Ant Metric (Jee) Average Dead Ant Metric (Jnn) Average Crossed Ant Metric Median chi^2 Per Antenna (Jee) Median chi^2 Per Antenna (Jnn)
2459855 digital_ok 0.00% 0.00% 0.00% 0.00% 4.58% 0.00% -0.053121 -0.145843 2.502452 -0.312378 -0.764800 0.416921 -0.894721 -0.781961 0.7098 0.7284 0.4249 1.432737 1.393088
2459854 digital_ok 0.00% 0.00% 0.00% 0.00% 8.93% 0.00% -0.214619 -0.241551 2.939787 0.486277 -0.751163 -0.602595 -0.814418 -0.541099 0.7243 0.7445 0.4329 1.430388 1.392450
2459853 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 0.290959 0.001044 4.153513 1.075058 -0.997299 -0.419048 -0.716269 -0.279600 0.7479 0.7056 0.4184 2.973632 2.808683
2459852 digital_ok 0.00% 0.00% 0.00% 0.00% 8.65% 1.62% 0.572050 0.533210 3.700927 0.780941 0.941216 0.219202 2.441535 0.510700 0.8312 0.8383 0.2410 2.816569 3.031596
2459847 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 0.809122 0.782127 6.422891 2.373292 -0.594362 -0.531833 -0.691933 0.086103 0.7361 0.7006 0.4219 3.012130 2.795108
2459846 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 1.551615 1.171436 4.966292 1.957238 2.324351 1.556854 -0.897180 -0.252425 0.8486 0.7001 0.4682 3.268942 3.306635
2459845 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 2.030750 1.490352 9.017231 4.296850 -0.712575 0.755041 -0.737789 -1.034129 0.7321 0.7473 0.3714 8.377589 13.472851
2459844 digital_ok 100.00% 100.00% 100.00% 0.00% - - 2.677287 0.615085 15.694559 13.506567 3.100808 2.967580 -0.686867 -0.874124 0.0264 0.0265 0.0007 nan nan
2459843 digital_ok 0.00% 0.66% 0.66% 0.00% 16.30% 0.00% 0.890671 0.976080 1.378174 2.637013 -0.810607 -1.175658 -0.863822 -0.668294 0.7444 0.7543 0.3732 1.754726 1.667221
2459840 digital_ok 0.00% 100.00% 100.00% 0.00% - - -0.537190 0.560437 0.653897 1.236908 0.892992 0.086882 -1.509530 -2.347300 0.0252 0.0256 0.0017 nan nan
2459839 digital_ok 100.00% - - - - - 0.123514 -0.110068 13.234670 14.288316 3.845041 3.614524 7.665696 4.098328 nan nan nan nan nan
2459838 digital_ok 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.134754 0.372845 1.967208 3.406256 -1.693491 -0.499379 -0.962333 -0.970755 0.7586 0.7340 0.3932 1.837344 1.493494
2459835 digital_ok 0.00% 100.00% 100.00% 0.00% - - -0.058612 -0.089545 1.415524 1.812162 -0.510581 1.151851 -0.559309 -0.877750 0.0414 0.0372 0.0005 nan nan
2459833 digital_ok 0.00% 100.00% 100.00% 0.00% - - -0.574479 0.559474 2.209368 3.098151 -0.088507 1.496214 -0.824716 -1.267363 0.0430 0.0647 0.0090 nan nan
2459832 digital_ok 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 1.099146 1.273175 1.315937 3.051195 -0.651990 1.157724 -0.704653 -1.115100 0.8148 0.5759 0.5465 1.598396 1.630285
2459831 digital_ok 100.00% 100.00% 55.11% 0.00% - - 0.110682 3.345320 16.530689 17.632962 6.286092 7.427778 -1.108251 -2.007899 0.1283 0.3308 0.0284 nan nan
2459830 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 1.530522 1.828379 2.269046 4.510849 0.242749 1.416139 -0.735016 -1.415053 0.8166 0.5969 0.5174 4.268482 4.637247
2459829 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 1.461122 1.515704 1.845289 4.424291 -0.983373 -0.246316 -0.065852 -0.945488 0.7675 0.7012 0.3847 8.242352 8.135374
2459828 digital_ok 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 1.538611 1.684048 1.357299 3.255663 0.704613 2.019863 -1.436626 -2.258855 0.8140 0.5993 0.5072 1.598835 1.426338
2459827 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 1.254420 1.513665 2.925876 5.914086 -0.784412 -0.181068 -0.669230 -0.709139 0.7699 0.7070 0.3890 11.014514 9.833194
2459826 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 1.721276 1.976640 2.711984 5.517362 1.003490 1.839593 -0.893805 -1.442627 0.8083 0.6057 0.4968 7.555245 8.649175
2459825 digital_ok 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 1.082894 1.495909 1.249545 3.372131 -0.302894 0.349071 -0.889003 -0.803950 0.8133 0.6331 0.4816 2.224819 2.144962
2459824 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 0.135685 0.368298 1.764234 4.634787 -1.206101 -0.359316 -0.477453 -0.402487 0.7391 0.7686 0.3521 6.357315 5.325988
2459823 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 2.001027 2.884907 2.433861 4.687827 1.513172 3.831000 -0.653437 -1.345082 0.7790 0.6899 0.4338 147.893082 62.287714
2459822 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 1.883061 2.438365 2.298280 4.713053 0.868873 1.980782 -0.585487 -0.882791 0.8095 0.6438 0.4795 5.325270 5.058635
2459821 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 2.985497 4.012967 2.259000 4.963449 -0.468798 1.081793 -1.584124 -0.940632 0.8118 0.6645 0.4752 4.809398 4.177107
2459820 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 1.900803 1.981217 2.690570 5.329116 0.555087 3.188974 -0.649889 -1.045337 0.7797 0.7206 0.4028 4.206135 4.426662
2459817 digital_ok 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 2.079706 3.282957 1.526681 3.878312 0.666932 3.617099 -0.749656 -0.848056 0.8207 0.6970 0.4725 1.757359 1.672309
2459816 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 1.904574 2.251964 2.340664 4.994552 1.619464 3.129430 -0.570299 -0.888557 0.8488 0.6294 0.5697 3.530372 3.578635
2459815 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 2.160645 3.117079 2.078628 4.478247 1.030457 3.320691 -1.152183 -1.411663 0.8201 0.7127 0.4767 3.587119 3.852336
2459814 digital_ok 0.00% - - - - - nan nan nan nan nan nan nan nan nan nan nan nan nan
2459813 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 3.564933 4.631314 1.645771 4.022010 1.392464 8.277987 0.185755 -0.345024 0.8015 0.7583 0.3749 14.922856 10.887344

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

In [11]:
htmls_to_display = []
for am_html in auto_metric_htmls:
    html_to_display = ''
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line:
            htmls_to_display.append(html_to_display)
            break

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.

In [12]:
for i, html_to_display in enumerate(htmls_to_display):
    if i == 100:
        break
    display(HTML(html_to_display))

Antenna 83: 2459855

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
83 N07 digital_ok ee Power 2.502452 -0.145843 -0.053121 -0.312378 2.502452 0.416921 -0.764800 -0.781961 -0.894721

Antenna 83: 2459854

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
83 N07 digital_ok ee Power 2.939787 -0.241551 -0.214619 0.486277 2.939787 -0.602595 -0.751163 -0.541099 -0.814418

Antenna 83: 2459853

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
83 N07 digital_ok ee Power 4.153513 0.001044 0.290959 1.075058 4.153513 -0.419048 -0.997299 -0.279600 -0.716269

Antenna 83: 2459852

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
83 N07 digital_ok ee Power 3.700927 0.572050 0.533210 3.700927 0.780941 0.941216 0.219202 2.441535 0.510700

Antenna 83: 2459847

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
83 N07 digital_ok ee Power 6.422891 0.782127 0.809122 2.373292 6.422891 -0.531833 -0.594362 0.086103 -0.691933

Antenna 83: 2459846

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
83 N07 digital_ok ee Power 4.966292 1.551615 1.171436 4.966292 1.957238 2.324351 1.556854 -0.897180 -0.252425

Antenna 83: 2459845

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
83 N07 digital_ok ee Power 9.017231 1.490352 2.030750 4.296850 9.017231 0.755041 -0.712575 -1.034129 -0.737789

Antenna 83: 2459844

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
83 N07 digital_ok ee Power 15.694559 2.677287 0.615085 15.694559 13.506567 3.100808 2.967580 -0.686867 -0.874124

Antenna 83: 2459843

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
83 N07 digital_ok nn Power 2.637013 0.976080 0.890671 2.637013 1.378174 -1.175658 -0.810607 -0.668294 -0.863822

Antenna 83: 2459840

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
83 N07 digital_ok nn Power 1.236908 -0.537190 0.560437 0.653897 1.236908 0.892992 0.086882 -1.509530 -2.347300

Antenna 83: 2459839

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
83 N07 digital_ok nn Power 14.288316 -0.110068 0.123514 14.288316 13.234670 3.614524 3.845041 4.098328 7.665696

Antenna 83: 2459838

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
83 N07 digital_ok nn Power 3.406256 0.372845 0.134754 3.406256 1.967208 -0.499379 -1.693491 -0.970755 -0.962333

Antenna 83: 2459835

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
83 N07 digital_ok nn Power 1.812162 -0.089545 -0.058612 1.812162 1.415524 1.151851 -0.510581 -0.877750 -0.559309

Antenna 83: 2459833

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
83 N07 digital_ok nn Power 3.098151 0.559474 -0.574479 3.098151 2.209368 1.496214 -0.088507 -1.267363 -0.824716

Antenna 83: 2459832

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
83 N07 digital_ok nn Power 3.051195 1.099146 1.273175 1.315937 3.051195 -0.651990 1.157724 -0.704653 -1.115100

Antenna 83: 2459831

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
83 N07 digital_ok nn Power 17.632962 0.110682 3.345320 16.530689 17.632962 6.286092 7.427778 -1.108251 -2.007899

Antenna 83: 2459830

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
83 N07 digital_ok nn Power 4.510849 1.530522 1.828379 2.269046 4.510849 0.242749 1.416139 -0.735016 -1.415053

Antenna 83: 2459829

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
83 N07 digital_ok nn Power 4.424291 1.515704 1.461122 4.424291 1.845289 -0.246316 -0.983373 -0.945488 -0.065852

Antenna 83: 2459828

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
83 N07 digital_ok nn Power 3.255663 1.684048 1.538611 3.255663 1.357299 2.019863 0.704613 -2.258855 -1.436626

Antenna 83: 2459827

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
83 N07 digital_ok nn Power 5.914086 1.254420 1.513665 2.925876 5.914086 -0.784412 -0.181068 -0.669230 -0.709139

Antenna 83: 2459826

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
83 N07 digital_ok nn Power 5.517362 1.976640 1.721276 5.517362 2.711984 1.839593 1.003490 -1.442627 -0.893805

Antenna 83: 2459825

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
83 N07 digital_ok nn Power 3.372131 1.495909 1.082894 3.372131 1.249545 0.349071 -0.302894 -0.803950 -0.889003

Antenna 83: 2459824

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
83 N07 digital_ok nn Power 4.634787 0.135685 0.368298 1.764234 4.634787 -1.206101 -0.359316 -0.477453 -0.402487

Antenna 83: 2459823

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
83 N07 digital_ok nn Power 4.687827 2.884907 2.001027 4.687827 2.433861 3.831000 1.513172 -1.345082 -0.653437

Antenna 83: 2459822

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
83 N07 digital_ok nn Power 4.713053 1.883061 2.438365 2.298280 4.713053 0.868873 1.980782 -0.585487 -0.882791

Antenna 83: 2459821

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
83 N07 digital_ok nn Power 4.963449 4.012967 2.985497 4.963449 2.259000 1.081793 -0.468798 -0.940632 -1.584124

Antenna 83: 2459820

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
83 N07 digital_ok nn Power 5.329116 1.900803 1.981217 2.690570 5.329116 0.555087 3.188974 -0.649889 -1.045337

Antenna 83: 2459817

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
83 N07 digital_ok nn Power 3.878312 2.079706 3.282957 1.526681 3.878312 0.666932 3.617099 -0.749656 -0.848056

Antenna 83: 2459816

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
83 N07 digital_ok nn Power 4.994552 2.251964 1.904574 4.994552 2.340664 3.129430 1.619464 -0.888557 -0.570299

Antenna 83: 2459815

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
83 N07 digital_ok nn Power 4.478247 3.117079 2.160645 4.478247 2.078628 3.320691 1.030457 -1.411663 -1.152183

Antenna 83: 2459814

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
83 N07 digital_ok nn Shape nan nan nan nan nan nan nan nan nan

Antenna 83: 2459813

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
83 N07 digital_ok nn Temporal Variability 8.277987 4.631314 3.564933 4.022010 1.645771 8.277987 1.392464 -0.345024 0.185755
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